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The Classification Gradient
Hong Kong August 20-August 24
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.111618th International Conference on Patt ...
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Vassili A. Kovalev, Maria Petrou, "The Classification Gradient," Pattern Recognition, International Conference on, vol. 3, pp. 830-833, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006.
 
 
BibTex
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@article{ 10.1109/ICPR.2006.1116,
author = {Vassili A. Kovalev and Maria Petrou},
title = {The Classification Gradient},
journal ={Pattern Recognition, International Conference on},
volume = {3},
year = {2006},
issn = {1051-4651},
pages = {830-833},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICPR.2006.1116},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Pattern Recognition, International Conference on
TI - The Classification Gradient
SN - 1051-4651
SP830
EP833
A1 - Vassili A. Kovalev,
A1 - Maria Petrou,
PY - 2006
KW - null
VL - 3
JA - Pattern Recognition, International Conference on
ER -
 
Vassili A. Kovalev, University of Surrey, UK
Maria Petrou, Imperial College, UK
We propose a method that uses bootstraping to classify the pixles in the two halves of a sliding window, assuming that if there is a real image boundary separating the two halves, the pixels in the two halves will be classified in two separate classes. The accuracy of the classification is used as a local "gradient". High values of this gradient allow us to detect weak statistical borders in 2D and 3D images.
Citation:
Vassili A. Kovalev, Maria Petrou, "The Classification Gradient," icpr, vol. 3, pp.830-833, 18th International Conference on Pattern Recognition (ICPR'06) Volume 3, 2006
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